Individual gene scores from a gene set analysis

Description

Compute individual gene scores from a gene set analysis

Usage

GSA.genescores(geneset.number, genesets,  GSA.obj,  genenames, negfirst=FALSE)

Arguments

Details

Compute individual gene scores from a gene set analysis. Useful for looking “inside” a gene set that has been called significant by GSA.

Value

A list with components

,

Author(s)

Robert Tibshirani

References

Efron, B. and Tibshirani, R. On testing the significance of sets of genes. Stanford tech report rep 2006. http://www-stat.stanford.edu/~tibs/ftp/GSA.pdf

Examples

######### two class unpaired comparison
# y must take values 1,2

set.seed(100)
x<-matrix(rnorm(1000*20),ncol=20)
dd<-sample(1:1000,size=100)

u<-matrix(2*rnorm(100),ncol=10,nrow=100)
x[dd,11:20]<-x[dd,11:20]+u
y<-c(rep(1,10),rep(2,10))


genenames=paste("g",1:1000,sep="")

#create some random gene sets
genesets=vector("list",50)
for(i in 1:50){
 genesets[[i]]=paste("g",sample(1:1000,size=30),sep="")
}
geneset.names=paste("set",as.character(1:50),sep="")

GSA.obj<-GSA(x,y, genenames=genenames, genesets=genesets,  resp.type="Two class unpaired", nperms=100)

# look at 10th gene set

GSA.genescores(10, genesets, GSA.obj, genenames)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(GSA)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/GSA/GSA.genescores.Rd_%03d_medium.png", width=480, height=480)
> ### Name: GSA.genescores
> ### Title: Individual gene scores from a gene set analysis
> ### Aliases: GSA.genescores
> ### Keywords: univar survival ts nonparametric
> 
> ### ** Examples
> 
> 
> ######### two class unpaired comparison
> # y must take values 1,2
> 
> set.seed(100)
> x<-matrix(rnorm(1000*20),ncol=20)
> dd<-sample(1:1000,size=100)
> 
> u<-matrix(2*rnorm(100),ncol=10,nrow=100)
> x[dd,11:20]<-x[dd,11:20]+u
> y<-c(rep(1,10),rep(2,10))
> 
> 
> genenames=paste("g",1:1000,sep="")
> 
> #create some random gene sets
> genesets=vector("list",50)
> for(i in 1:50){
+  genesets[[i]]=paste("g",sample(1:1000,size=30),sep="")
+ }
> geneset.names=paste("set",as.character(1:50),sep="")
> 
> GSA.obj<-GSA(x,y, genenames=genenames, genesets=genesets,  resp.type="Two class unpaired", nperms=100)
perm= 10 / 100 
perm= 20 / 100 
perm= 30 / 100 
perm= 40 / 100 
perm= 50 / 100 
perm= 60 / 100 
perm= 70 / 100 
perm= 80 / 100 
perm= 90 / 100 
perm= 100 / 100 
> 
> # look at 10th gene set
> 
> GSA.genescores(10, genesets, GSA.obj, genenames)
      Gene   Score   
 [1,] "g53"  "1.112" 
 [2,] "g916" "0.845" 
 [3,] "g10"  "0.714" 
 [4,] "g598" "0.584" 
 [5,] "g944" "0.493" 
 [6,] "g367" "0.46"  
 [7,] "g577" "0.414" 
 [8,] "g629" "0.33"  
 [9,] "g422" "0.228" 
[10,] "g950" "0.181" 
[11,] "g498" "0.175" 
[12,] "g226" "0.149" 
[13,] "g821" "0.076" 
[14,] "g604" "0.069" 
[15,] "g255" "-0.005"
[16,] "g903" "-0.01" 
[17,] "g842" "-0.047"
[18,] "g60"  "-0.047"
[19,] "g1"   "-0.081"
[20,] "g696" "-0.185"
[21,] "g48"  "-0.242"
[22,] "g499" "-0.243"
[23,] "g261" "-0.289"
[24,] "g562" "-0.292"
[25,] "g306" "-0.314"
[26,] "g811" "-0.462"
[27,] "g578" "-0.53" 
[28,] "g679" "-0.584"
[29,] "g831" "-0.61" 
[30,] "g739" "-0.714"
> 
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>